A method is known in which an object (a surface thereof) is photographed and the image data acquired by the photographing is examined, thereby detecting the direction in which that specific surface (hereinafter called “object surface”) is orientated. Various methods may be employed to examine the image data. One of the methods is template mapping method. In the template mapping method, the image of the object surface photographed is compared with the images of the object surface, i.e., so-called templates, which have been photographed and stored, thereby to detect the similarity the image photographed now has with respected to the templates. That is, the object surface photographed now is regarded as orientated in the very direction in which the template of the highest similarity is orientated.
In the template mapping method, however, the similarity detected changes, once the features (e.g., position, rotation and size) of the image photographed have changed, even if the orientation (e.g., angle) of the object surface remains almost the same. Consequently, the orientation (angle) finally detected of the object surface may differ from the actual value. In other words, the template mapping method has but low robustness to the changes in the features of the image photographed.
A method is available, in which a search provided in the object surface is photographed by moving the photographing apparatus in parallel to the object surface and in a direction perpendicular thereto, and by performing zooming. The image data thus acquired is used, thereby detecting the similarity. Thus, the orientation (angle) of the object surface can be correctly detected even if the image photographed changes somewhat. In this method, however, the amount of data processed increases, and the calculation proportionally increases. The method is disadvantageous in that much time is required to detect the orientation of the object surface. There is another problem with the method. If any other part of the object surface, other than the search area, changes in its displayed state, the angle cannot be detected accurately.
With the template mapping method it is difficult to distinguish one part of the object surface form another of the same color, particularly when the entire image of the object surface has a low luminance. That is, parts of the same colors cannot be distinguished in accordance with the luminance of one of the pixels that constitute the image. For example, images of brown hair and brown eye can hardly be distinguished from each other. Since the image of the brown eye cannot be distinguished from that of the brown hair, it is impossible to detect the orientation of the face from the image of the eyes that are facial features more prominent than the hair. Further, the difference in pixel value between the image of the eye and the image of the skin differs, from person to person. For example, the difference is small for a person who has brown skin and brown eyes, whereas the difference is large for a person who has fair kin and brown eyes. The images of, for example, the eyes cannot be reliably extracted from the face images of all persons. Therefore, the template mapping method is disadvantageous for its low robustness to the changes in the features of the image photographed.